Infectious Disease Epidemiology

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Infectious Disease Epidemiology

• Sharyn Orton, Ph.D.
• American Red Cross, Rockville, MD
• Suggested reading
• Modern Infectious Disease Epidemiology (1994) by
  Johan Giesecke
• Modern Epidemiology (1998) by Kenneth Rothman and
  Sander Greenland

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My interest in infectious disease epidemiology
stems from my 20 years as a Medical
Technologist. An advanced degree in Epidemiology
and Biostatistics has enabled me to better
understand the dynamics and power of infectious
disease epidemics, as well as the important
differences from diseases caused by non
infectious agents.
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Learning/Performance Objectives 1. Understand the
unique differences between infectious and
non- infectious disease epidemiology. 2.
Understand the terminology. 3. Be able to
calculate sensitivity, specificity, predictive
values and transmission probabilities.
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Features unique to infectious diseases 1. A case
may also be a source. 2. People may be immune. 3.
A case may be a source without being
recognized. 4. There is often a need for
urgency. 5. Preventive measures often have good
scientific basis.
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Outcomes of exposure 1. No infection 2. Clinical
infection resulting in death, immunity, carrier
or non-immunity 3. Sub-clinical infection
resulting in immunity, carrier or
non-immunity 4. Carrier
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Definitions 1. Incidence 2. Prevalence 3. Attack
rate 4. Primary/secondary cases 5. Case fatality
rate or ratio 6. Virulence
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Definitions continued 7. Mortality 8.
Reproductive rate 9. Vector 10. Transmission
routes 11. Reservoir vs source 12. Zoonosis
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Definitions continued 13. Incubation period 14.
Serial interval 15. Infectious period 16. Latent
period 17. Epidemic
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Mathematical Models for Epidemics Person to
person spread relies on the reproduction rate,
which is the average number of people infected by
one case. This is influenced by the attack rate
of disease, the frequency of contact, the
duration of infectivity and the immune status of
the population.
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Outbreak Analysis Early analysis Person who is
the case? Place where was the case
infected? Time when was the case infected?
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Outbreak Analysis continued Epidemic Curve 1.
Plot the date on the horizontal axis. 2. Plot
the number of cases on the vertical axis. 3.
Determine if the outbreak is point source,
continuous or person to person.
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Outbreak Analysis continued Check the
geography. Check the age and sex.
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Factors Affecting Surveillance Outbreak
discovery Outbreak analysis Validity of
notification data Notification delays Information
feedback Sources of data
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Factors Affecting Infectivity Dose and
route Immunity Co-factors Subclinical infection
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Seroepidemiology Used for 1. Description of
seroprevalence in populations 2. Follow
incidence by estimation from changes using
multiple samples from a population
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Seroepidemiology continued Importance of case and
control classification Use of a gold standard
reference. Use of clinical diagnosis.
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Seroepidemiology continued Sensitivity Specificity
Positive predictive value Negative predictive
value Pre-test probability of disease
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Contact Patterns Use graphs or matrices to
describe the network of contacts. Study the
networks by interviewing the cases about their
contacts. Study the contact structure.
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Transmission Probability Ratio TPR is a measure
of risk of transmission from infected to
susceptible individuals during a contact. For any
given type of contact or agent, an estimate of
the effect of a covariate on susceptibility,
infectiousness or both can be made.
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TPR continued TPR of differing types of contacts,
infectious agents, infection routes or strains
can be calculated. There are 4 types of
transmission probabilities (tp).
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Binomial Transmission Probabilities Used when
susceptibles make more than one potentially
infectious contact. The maximum likelihood
estimate of the tp under the binomial model of
susceptibles who become infected ? total number
of contacts with infectives
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Study Designs Cross-sectional risk or prevalence
ratio Case control odds ratio Cohort relative
risk Survival analysis
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Study Issues Confounding Bias Misclassification I
nteraction
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Epidemiology of vaccination Direct immunity by
infection or vaccination Indirect herd
immunity Vaccine efficacy () Iu-Iv/Iu x 100
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Conclusion Infectious and non-infectious
disease epidemiology have important differences
due to the inherently different nature of the
risk factors (biological agent i.e. virus,
bacteria vs chemical, environmental or genetic).
It is important to understand and consider these
differences when conducting infectious disease
research.